Refined modeling and trajectory tracking method of vehicle model considering vertical load

Abstract

The present invention discloses a vehicle model refinement modeling and trajectory tracking method considering the vertical load of tires. During the driving process of the vehicle, firstly, by considering the dynamic vertical load change of the tires during the driving process of the vehicle, the dynamic load of the tires is calculated, and the appropriate tire model is dynamically selected to establish an accurate vehicle dynamics model, and then the vehicle motion controller considering the vertical load change is designed. Through the vehicle motion controller, the front wheel angle and four-wheel torque of the vehicle are obtained in combination with the real-time state information of the vehicle, so as to realize the accurate trajectory tracking of the distributed electric vehicle. The present invention ensures that the vehicle can realize accurate modeling and accurate trajectory tracking of the vehicle under various driving conditions by considering the changes of real-time information and load, thereby improving the safety and adaptability of the vehicle.

Description

Technical Field

[0001] The invention belongs to the technical field of fine modeling and trajectory tracking of electric vehicles, and in particular relates to a vehicle model fine modeling and trajectory tracking method taking into account the vertical load of tires. Background Art

[0002] In recent years, distributed electric vehicles have not only improved the vehicle's power performance and response speed, but also brought higher control accuracy and flexibility, thanks to their high controllable freedom, compact structure, efficient transmission system, and large control redundancy. This has created more opportunities and challenges for the development of chassis electronic control systems, and has become an important direction for the development of new energy vehicles. The driving safety of vehicles is the core issue of vehicle development. The active safety technology of vehicles can improve the driving safety of vehicles and the accuracy of trajectory tracking. This technology has always been a research hotspot in the automotive industry and academia. Therefore, the design of an effective and reliable on-board controller is of great significance to improving the driving safety and trajectory tracking accuracy of distributed electric vehicles.

[0003] To improve the driving safety of distributed electric vehicles, it is first necessary to accurately model the vehicle. As the only medium for the vehicle to contact the ground, the vertical load of the tire will directly affect the ground contact area of ​​the tire, as well as the lateral and longitudinal forces generated by the friction between the tire and the ground, thereby affecting the accuracy of the vehicle's trajectory tracking and driving safety. During the dynamic driving of the vehicle, the tire load may fluctuate greatly, and the dynamic load will deviate significantly from the static load. The load change will affect the mechanical properties of the tire, resulting in the static parameters of the tire being unable to apply to a variety of driving conditions, thereby affecting the vehicle's handling performance. Therefore, real-time monitoring of the difference between the vertical load and the static load of the tire, and dynamically adjusting the tire model can more accurately describe the mechanical properties of the tire, thereby improving the stability, accuracy and adaptability of the vehicle under various dynamic trajectory tracking conditions.

[0004] During vehicle driving, we first consider the changes in the dynamic vertical load of the tires during vehicle driving, combine them with the dynamic tire model, and establish an accurate vehicle model. Then, we design a vehicle motion controller that takes the changes in vertical loads into consideration. Through the real-time status information of the vehicle, we can achieve accurate trajectory tracking of distributed electric vehicles, thereby improving the safety and adaptability of the vehicle. Summary of the invention

[0005] In order to solve the problem of reduced model accuracy and control deviation caused by the change of tire vertical load during the driving of distributed electric vehicles, the present invention proposes a vehicle model refinement modeling and trajectory tracking method considering the tire vertical load. During the driving of the vehicle, firstly, by considering the change of dynamic vertical load of the tire during the driving of the vehicle, the dynamic load of the tire is calculated, and the appropriate tire model is dynamically selected to establish an accurate vehicle dynamics model, and then the vehicle motion controller considering the change of vertical load is designed. Through the vehicle motion controller, the front wheel angle and four-wheel torque of the vehicle are obtained in combination with the real-time status information of the vehicle, so as to realize the accurate trajectory tracking of the distributed electric vehicle. The present invention ensures that the vehicle can realize accurate modeling and accurate trajectory tracking of the vehicle under various driving conditions by considering the change of real-time information and load, thereby improving the safety and adaptability of the vehicle.

[0006] In order to realize the above functions, the present invention provides the following technical solutions:

[0007] A vehicle model refinement modeling and trajectory tracking method considering tire vertical loads includes the following steps:

[0008] Step 1: Establish a vehicle reference model, and obtain a reference value of vehicle state information according to the vehicle reference model, expected speed, and expected path;

[0009] Step 2: Consider the change of the vertical dynamic load of the tire during the driving process of the vehicle, dynamically select the tire model under different driving conditions according to the dynamic load transfer index, obtain the longitudinal and lateral forces of the tire through the tire model, and use the tire force to build the vehicle dynamics model;

[0010] Step 3: discretize the vehicle dynamics model established in step 2 to obtain the MPC prediction equation;

[0011] Step 4: Based on the MPC prediction equation determined in step 3, the optimization problem of the vehicle motion controller considering the vertical load change is constructed through the cost function and constraint conditions, and the solved control quantity is fed back to the vehicle reference model to complete the closed-loop control of the vehicle.

[0012] Furthermore, the step 1 comprises:

[0013] A vehicle reference model is selected according to the vehicle's motion characteristics, and the vehicle reference model includes the vehicle's lateral and longitudinal rigid body motions and yaw motions;

[0014] The desired vehicle speed and the lateral and longitudinal displacements of the desired path are input into the vehicle reference model, that is:

[0015] ;

[0016] ;

[0017] ;

[0018] in, is the reference value of the vehicle's longitudinal speed; is the input desired vehicle speed; are the longitudinal displacement and lateral displacement of the vehicle in the geodetic coordinate system respectively; are the reference values ​​of the longitudinal displacement and lateral displacement of the vehicle in the geodetic coordinate system respectively;

[0019] Reference value of vehicle lateral speed during vehicle driving The calculation formula is:

[0020] ;

[0021] in, are the distances from the vehicle's center of gravity to the front and rear wheels respectively; is the understeer coefficient; is the front wheel turning angle; is the actual longitudinal speed of the vehicle; is the acceleration due to gravity;

[0022] Reference value of vehicle yaw rate during vehicle driving The calculation formula is:

[0023] .

[0024] Furthermore, the step 2 comprises:

[0025] S21. Receive the real-time status information and parameter information of the vehicle during driving, and calculate the real-time vertical dynamic load values ​​of the four wheels during driving of the vehicle through the calculation model of the vertical dynamic load of the tire;

[0026] S22. Based on the vertical dynamic load and vertical static load of the wheel, a wheel load transfer index calculation model is constructed to calculate the load transfer indexes of the four wheels in real time. ;

[0027] S23. Real-time load transfer index of four wheels With the set threshold Compare and dynamically select tire models during vehicle driving;

[0028] S24. Through dynamic selection of tire models, the tire lateral force and tire longitudinal force are obtained using the vertical load transfer coefficient of the wheel under various driving conditions, thereby constructing a vehicle dynamics model.

[0029] Furthermore, in step S21, the tire vertical dynamic load calculation formula is as follows:

[0030] ;

[0031] ;

[0032] in, are the vertical dynamic loads of the four wheels respectively; For the front and rear wheels of the vehicle; For the left and right wheels of the vehicle; is the distance from the front wheel to the rear wheel of the vehicle, ; is the mass of the vehicle; is the height of the vehicle’s center of mass; are the longitudinal and lateral accelerations of the vehicle respectively; They are the front and rear wheelbases of the vehicle respectively.

[0033] Furthermore, in step S22, the wheel load transfer index calculation model is as follows:

[0034] ;

[0035] in,, is the real-time dynamic load transfer index of the four wheels; is the static load of the four wheels;

[0036] The static load calculation formula of the wheel is as follows:

[0037] ;

[0038] ;

[0039] in, is the mass of the vehicle; is the acceleration due to gravity; is the distance from the front wheel to the rear wheel of the vehicle; are the distances from the center of gravity of the vehicle to the front and rear wheels respectively.

[0040] Further, the step S23 includes:

[0041] 1) If the wheel load transfer index does not exceed the threshold, that is , the mechanical behavior of the tire is described by static parameters, namely:

[0042] ;

[0043] ;

[0044] in, They are the longitudinal and lateral forces of the four wheels respectively; are the longitudinal and lateral stiffness coefficients of the wheel respectively; are the longitudinal slip rates of the four wheels respectively; is the lateral slip angle of the four wheels;

[0045] ;

[0046] ;

[0047] in, is the four-wheel speed; is the effective rolling radius of the wheel; is the lateral speed of the vehicle;

[0048] 2) If the load transfer index of the wheel exceeds the threshold, that is , the longitudinal and lateral forces of the wheel are calculated by the nonlinear tire model, and the calculation formula is as follows:

[0049] ;

[0050] ;

[0051] in, is the peak factor; is the curve shape factor; is the curve curvature factor.

[0052] Furthermore, in step S24, the vehicle dynamics model is as follows:

[0053] ;

[0054] in, They are the longitudinal and lateral forces provided by the wheels respectively.

[0055] Furthermore, the step three comprises:

[0056] The state space equation is established through the vehicle dynamics model established in step 2. The control variables, state variables and output variables of the vehicle motion controller are:

[0057] ;

[0058] ;

[0059] ;

[0060] ;

[0061] in, They are the torque values ​​of the left front, right front, left rear and right rear wheels respectively, and their calculation relationship with the longitudinal force of the tire is:

[0062] ;;

[0063] The continuous state equation of the vehicle is discretized, and the nonlinear prediction equation for predicting the future state of the vehicle is expressed as:

[0064] ;

[0065] ;

[0066] Based on the model predictive control principle, according to the measured value and prediction model of the current control system state, at the current moment , the reference matrix of the future input variables, output variables, and state variables of the prediction system is expressed as:

[0067] ;

[0068] ;

[0069] ;

[0070] in, For the prediction time domain; To control the time domain, .

[0071] Furthermore, the step 4 includes:

[0072] The cost function is constructed by the reference value of the vehicle's relevant state information, the difference between the vehicle state quantity and the expected value in the control time domain, and the change value of the control quantity:

[0073] To ensure that the vehicle tracks the expected speed and expected path, the cost function Expressed as:

[0074] ;

[0075] in, is the weight coefficient;

[0076] In order to reduce the fluctuation of the control quantity, the cost function and Expressed as:

[0077] ;

[0078] ;

[0079] in, is the weight coefficient of each part of the loss function;

[0080] Therefore, the overall cost function of the optimization problem is expressed as:

[0081] ;

[0082] Set the relevant constraints of the optimization problem. Considering the physical constraints of the vehicle during driving, the optimization problem can be summarized as follows:

[0083] ;

[0084] The control quantity is solved and fed back to the vehicle reference model to complete the closed-loop control of the vehicle.

[0085] Compared with the prior art, the present invention has the following positive effects:

[0086] 1. The present invention takes into account the vertical load transfer of the wheels during vehicle driving. During dynamic driving, especially in conditions of rapid acceleration, braking or high-speed turning, the loads on the front and rear wheels of the vehicle will change, and the vertical load of the tire will directly affect the tire's contact area and the lateral and longitudinal forces generated by the friction between the tire and the ground, thereby affecting the vehicle's control performance. Therefore, considering the vertical load transfer of the vehicle can be closer to the actual working conditions and provide a basis for accurate trajectory tracking.

[0087] 2. The present invention dynamically selects a suitable tire model based on the vertical load transfer index of the wheel. Tire models usually rely on experimental data and parameterization methods. These parameters are usually calibrated within a specific load range. When the vertical load of the tire changes significantly, it will affect the mechanical properties of the tire, causing the static parameters assumed in the tire model to no longer be applicable. Therefore, by real-time monitoring of the difference between the vertical dynamic load and the static load, and dynamically adjusting the tire model or its parameters, the mechanical behavior of the tire can be more accurately described.

[0088] 3. The present invention proposes accurate vehicle modeling and trajectory tracking that takes into account the vertical load transfer of the wheels. As the only medium for the vehicle to contact the ground, the accuracy of the tire model will directly affect the accuracy of the vehicle model, and thus affect the vehicle's handling performance. Therefore, using the dynamic adjustment of the tire model to model the vehicle not only improves the accuracy of the vehicle model, but also improves the vehicle stability and control accuracy of the vehicle in various trajectory tracking. BRIEF DESCRIPTION OF THE DRAWINGS

[0089] The accompanying drawings referred to below will describe the present invention in more detail and clarity. The accompanying drawings herein constitute a part of this specification and are used together with the embodiments of the present invention to explain the principles of the present invention. Among them:

[0090] Figure 1It is a vehicle model with four-wheel independent drive and front-wheel steering in an embodiment of the present invention.

[0091] Figure 2 It is a simple model of the tire in the embodiment of the present invention.

[0092] Figure 3 2 is a diagram of an overall control architecture of an embodiment of the present invention.

[0093] Figure 4 4 is a schematic diagram of a vehicle motion controller that takes vertical load changes into consideration in an embodiment of the present invention. DETAILED DESCRIPTION

[0094] The purpose of the present invention is to consider the dynamic changes of the vertical load on the wheels during the driving process of the vehicle, and to propose a vehicle model refinement modeling and trajectory tracking method. Figures 1 to 4 The theoretical knowledge, formulas and advantages and features involved in the implementation of the present invention are further elaborated in detail.

[0095] Embodiment 1: This embodiment is a vehicle model refinement modeling and trajectory tracking method considering tire vertical load, comprising the following steps:

[0096] Step 1: Establish a vehicle reference model, and obtain a reference value of the vehicle state information according to the vehicle reference model, the expected speed, and the expected path.

[0097] According to the motion characteristics of the vehicle and the research features of the present invention, a vehicle reference model is selected. In this embodiment, the vehicle is set as a distributed electric vehicle with four-wheel independent drive and front-wheel steering; the reference model includes the lateral and longitudinal rigid body motion and yaw motion of the vehicle.

[0098] In order to ensure that the vehicle can meet the expected driving requirements, the expected vehicle speed and the lateral and longitudinal displacements of the expected path are input into the reference model, that is:

[0099] ;

[0100] ;

[0101] ;

[0102] in, is the reference value of the vehicle's longitudinal speed; is the input desired vehicle speed; are the longitudinal displacement and lateral displacement of the vehicle in the geodetic coordinate system respectively; are the reference values ​​of the longitudinal displacement and lateral displacement of the vehicle in the geodetic coordinate system, respectively.

[0103] In order to ensure the driving safety of the vehicle, it is expected that the lateral speed of the vehicle during driving can meet the expected trajectory requirements, that is:

[0104] ;

[0105] in, is the reference value of the vehicle's lateral speed; are the distances from the vehicle's center of gravity to the front and rear wheels respectively; is the understeer coefficient, which is a constant; is the front wheel turning angle ( ); is the actual longitudinal speed of the vehicle; is the acceleration due to gravity. Figure 1 As shown, during the vehicle driving process, the reference value calculation formula of the yaw angular velocity is as follows:

[0106] ;

[0107] in, is the reference value of the vehicle's yaw rate.

[0108] Using the vehicle reference model, with the expected speed and expected path as input, the real-time reference value of the relevant vehicle status information during the vehicle's driving process is obtained:

[0109] ;

[0110] in, is the reference value matrix of the state variables required by the vehicle motion controller.

[0111] Step 2: Consider the change of tire vertical dynamic load during vehicle driving, dynamically select tire models under different driving conditions according to the dynamic load transfer index, obtain accurate tire longitudinal and lateral forces through the tire model, and use tire forces to build a vehicle dynamics model.

[0112] S21. Receive real-time status information and parameter information of the vehicle during driving, such as longitudinal and lateral accelerations and center of mass height, etc.; calculate the real-time vertical dynamic load values ​​of the four wheels during driving of the vehicle through the calculation model of the vertical dynamic load of the tire; the calculation formula of the vertical dynamic load of the tire is as follows:

[0113] ;

[0114] ;

[0115] in,, are the vertical dynamic loads of the four wheels respectively; For the front and rear wheels of the vehicle; For the left and right wheels of the vehicle; is the distance from the front wheel to the rear wheel of the vehicle, ; is the mass of the vehicle; is the height of the vehicle’s center of mass; are the longitudinal and lateral accelerations of the vehicle respectively; They are the front and rear wheelbases of the vehicle respectively.

[0116] By calculating the vertical dynamic loads of the four wheels in real time, a basis is provided for the subsequent calculation of the load transfer index of the four wheels.

[0117] S22. A wheel load transfer index calculation model is constructed based on the vertical dynamic load and the vertical static load of the wheel. The wheel load transfer index calculation model is as follows:

[0118] ;

[0119] in, is the real-time dynamic load transfer index of the four wheels; is the static load of the four wheels;

[0120] The static load of the wheel is related to the weight of the vehicle and related vehicle parameters, and its calculation formula is as follows:

[0121] ;

[0122] ;

[0123] Through the real-time vertical dynamic load and vertical static load of the tire, the load transfer index of the four wheels is calculated in real time during the vehicle driving process, providing a data basis for the subsequent selection of the tire model.

[0124] S23. Real-time load transfer index of four wheels With the set threshold Compare and determine whether a large load transfer occurs on each wheel, and dynamically select the tire model during vehicle driving:

[0125] 1) If the wheel load transfer index does not exceed the threshold, that is , it means that the static parameters can accurately describe the mechanical behavior of the tire, namely:

[0126] ;

[0127] ;

[0128] in, They are the longitudinal and lateral forces of the four wheels respectively; are the longitudinal and lateral stiffness coefficients of the wheels respectively (the parameters of the four wheels are consistent); are the longitudinal slip rates of the four wheels respectively; is the lateral slip angle of the four wheels; Figure 2 As shown, the relevant calculation method is as follows:

[0129] ;

[0130] ;

[0131] in, is the four-wheel speed; is the effective rolling radius of the wheel; is the lateral velocity of the vehicle.

[0132] 2) If the load transfer index of the wheel exceeds the threshold, that is , the static linear parameters can no longer meet the accuracy requirements of the calculation, so the longitudinal and lateral forces of the wheel will be calculated through the nonlinear tire model (Paceika model), and the calculation formulas are as follows:

[0133] ;

[0134] ;

[0135] in, is the peak factor; is the curve shape factor; is the curve curvature factor, and its value is related to the selection of tire model. This nonlinear tire model ensures the calculation accuracy of tire force in all directions of the wheel under the condition of large vertical load transfer.

[0136] By dynamically selecting the tire model during vehicle driving, accurate tire force is provided for subsequent vehicle model establishment and control, thereby ensuring the accuracy of vehicle modeling and trajectory tracking.

[0137] S24. Through the above dynamic tire model selection, under various driving conditions, the vertical load transfer coefficient of the wheel is used to obtain accurate tire lateral force and tire longitudinal force, thereby constructing a vehicle dynamics model, such as Figure 1 As shown, the vehicle dynamics model is as follows:

[0138] ;

[0139] in, They are the longitudinal and lateral forces provided by the wheels, and the calculation formula is as follows:

[0140] ;

[0141] ;

[0142] ;

[0143] ;

[0144] ;

[0145] ;

[0146] ;

[0147] ;

[0148] Through the 3DOF vehicle dynamics model, the changes in vehicle-related state information under different driving conditions are accurately described, providing accurate data for the model prediction equation of the subsequent vehicle motion controller.

[0149] Step 3: Discretize the vehicle dynamics model established in step 2 to obtain the MPC prediction equation:

[0150] The state space equations are established through the vehicle dynamics model established in step 2. The control variables, state variables and output variables of the vehicle motion controller are as follows:

[0151] ;

[0152] ;

[0153] ;

[0154] ;

[0155] in, They are the torque values ​​of the left front, right front, left rear, and right rear wheels, and their calculation relationship with the tire longitudinal force is as follows:

[0156] ;

[0157] The continuous state equation of the vehicle is discretized, so the nonlinear prediction equation for predicting the future state of the vehicle can be expressed as follows:

[0158] ;

[0159] ;

[0160] Based on the model predictive control principle, the future state of the system can be predicted based on the measured value of the current control system state and the prediction model. , the reference matrix of the system's future input and output variables and state variables can be expressed as follows:

[0161] ;

[0162] ;

[0163] ;

[0164] in, For the prediction time domain; To control the time domain, .

[0165] This step uses the vehicle dynamics model and model predictive control principles to obtain the precise changes in state variables in the prediction time domain and discretize them, providing a basis for solving the optimization problem of the vehicle motion controller.

[0166] Step 4: Based on the MPC prediction equation determined in step 3, the optimization problem of the vehicle motion controller considering the vertical load change is constructed through the cost function and constraint conditions, and the solved control quantity is fed back to the vehicle reference model to complete the closed-loop control of the vehicle.

[0167] The cost function is constructed by using the reference value of the vehicle's relevant state information, the difference between the vehicle state and the expected value in the control time domain, and the change value of the control quantity:

[0168] To ensure that the vehicle can accurately track the expected speed and expected path, the cost function It can be expressed as follows:

[0169] ;

[0170] in, is the weight coefficient;

[0171] The large fluctuation of the control variable will reduce the overall efficiency of the vehicle and affect the sustainability of operation. Therefore, it is necessary to reduce the fluctuation of the control variable. To achieve this control goal, the cost function and As shown below:

[0172] ;

[0173] ;

[0174] in, is the weight coefficient of each part of the loss function.

[0175] Therefore, the overall cost function of the optimization problem can be expressed as follows:

[0176] ;

[0177] Set the relevant constraints of the optimization problem. Considering the physical constraints during vehicle driving, the optimization problem can be summarized as:

[0178] ;

[0179] The control quantity is solved and fed back to the vehicle reference model to complete the closed-loop control of the vehicle. This ensures that the control quantity obtained meets the actual physical constraints of the vehicle based on the vehicle model considering the vertical load, and can improve the accuracy and control performance of the vehicle under various trajectory tracking conditions.

[0180] This embodiment first obtains the reference value of the vehicle state information based on the vehicle reference model and the expected speed and path; then considers the change of the vertical dynamic load of the tire during the vehicle driving process, and obtains a more accurate tire model under different driving conditions based on the dynamic load transfer index, and obtains accurate tire longitudinal and lateral forces through the tire model, and uses the tire force to build a vehicle dynamics model; discretizes the dynamic model to obtain the prediction equation, and constructs the optimization problem of the vehicle motion controller considering the vertical load change through the cost function and constraint conditions, and finally feeds the solved control quantity back to the reference model to complete the closed-loop control of the vehicle. Through the above steps, the refined modeling of the vehicle model considering the vertical load and the accurate trajectory tracking strategy can be achieved.

Claims

1. A vehicle model refinement modeling and trajectory tracking method considering tire vertical load, characterized in that: The following steps are involved: Step 1: Establish a vehicle reference model, and obtain a reference value of vehicle state information according to the vehicle reference model, expected speed, and expected path; Step 2: Consider the change of the vertical dynamic load of the tire during the driving process of the vehicle, dynamically select the tire model under different driving conditions according to the dynamic load transfer index, obtain the longitudinal and lateral forces of the tire through the tire model, and use the tire force to build the vehicle dynamics model; Step 3: discretize the vehicle dynamics model established in step 2 to obtain the MPC prediction equation; Step 4: Based on the MPC prediction equation determined in step 3, the optimization problem of the vehicle motion controller considering the vertical load change is constructed through the cost function and the constraint conditions, and the control quantity u solved by the vehicle motion controller optimization problem is fed back to the vehicle reference model to complete the closed-loop control of the vehicle.

2. The vehicle model refinement modeling and trajectory tracking method considering tire vertical load as claimed in claim 1, characterized in that: The step one comprises: A vehicle reference model is selected according to the vehicle's motion characteristics, and the vehicle reference model includes the vehicle's lateral and longitudinal rigid body motions and yaw motions; The desired vehicle speed and the lateral and longitudinal displacements of the desired path are input into the vehicle reference model, that is: V x,ref =V x,in x v =x v,ref and v =and v,ref Among them, V x,ref is the reference value of the vehicle longitudinal speed; V x,in is the expected vehicle speed input; x v ,y v are the longitudinal displacement and lateral displacement of the vehicle in the geodetic coordinate system respectively; v,ref ,y v,ref are the longitudinal displacement reference value and the lateral displacement reference value of the vehicle in the geodetic coordinate system respectively; During the vehicle driving process, the reference value V of the vehicle's lateral speed y,ref The calculation formula is: Among them, l f , l r are the distances from the center of gravity of the vehicle to the front and rear wheels respectively; Γ u is the understeer coefficient; δ f is the front wheel turning angle; V x is the actual longitudinal speed of the vehicle; g is the acceleration due to gravity; Reference value of vehicle yaw rate during vehicle driving The calculation formula is:

3. The vehicle model refinement modeling and trajectory tracking method considering tire vertical load as claimed in claim 1, characterized in that: The second step comprises: S21. Receive the real-time status information and parameter information of the vehicle during driving, and calculate the real-time vertical dynamic load values ​​of the four wheels during driving of the vehicle through the calculation model of the vertical dynamic load of the tire; S22. Based on the vertical dynamic load and vertical static load of the wheel, a wheel load transfer index calculation model is constructed to calculate the four wheel load transfer indexes LTI in real time. ij ; S23. The real-time load transfer index LTI of the four wheels ij With the set threshold Compare and dynamically select tire models during vehicle driving; S24. Through dynamic selection of tire models, under various driving conditions, the tire lateral force and tire longitudinal force are obtained using the vertical load transfer coefficient of the wheel, thereby constructing a vehicle dynamics model.

4. The vehicle model refinement modeling and trajectory tracking method considering tire vertical load as claimed in claim 3, characterized in that: In step S21, the calculation formula of the tire vertical dynamic load is as follows: in, is the vertical dynamic load of the four wheels, i = {f, r} is the front and rear wheels of the vehicle, j = l, r is the left and right wheels of the vehicle; l is the distance from the front wheel to the rear wheel of the vehicle, l = l f +l r , l f , l r are the distances from the center of gravity of the vehicle to the front and rear wheels respectively; m is the mass of the vehicle; h is the height of the center of mass of the vehicle; a x 、a y are the longitudinal and lateral accelerations of the vehicle respectively; t f ,t r They are the front and rear wheelbases of the vehicle respectively.

5. The vehicle model refinement modeling and trajectory tracking method considering tire vertical load as claimed in claim 3, characterized in that: In step S22, the wheel load transfer index calculation model is as follows: Among them, LTI ij is the real-time dynamic load transfer index of the four wheels; F sl,ij is the vertical static load of the four wheels; is the vertical dynamic load of the four wheels, i = {f, r} is the front and rear wheels of the vehicle, j = {l, r} is the left and right wheels of the vehicle; The static load calculation formula of the wheel is as follows: Where m is the mass of the vehicle; g is the acceleration due to gravity; l is the distance from the front wheel to the rear wheel of the vehicle; l f , l r are the distances from the center of gravity of the vehicle to the front and rear wheels respectively.

6. The vehicle model refinement modeling and trajectory tracking method considering tire vertical load as claimed in claim 3, characterized in that: The step S23 comprises: 1) If the wheel load transfer index does not exceed the threshold, that is i={f,r},j={l,r}, then the mechanical behavior of the tire is described by static parameters, namely: F x,ij =B x λ ij ,i={f,r},j={l,r} F y,ij =B y α ij ,i={f,r},j={l,r} Among them, F x,ij 、F y,ij ,i={f,r},j={l,r} are the longitudinal and lateral forces of the four wheels respectively; B x , B y are the longitudinal and lateral stiffness coefficients of the wheel respectively; ij are the longitudinal slip rates of the four wheels respectively; α ij is the lateral slip angle of the four wheels; α ij =tan -1 (V y / V x ),i={f,r},j={l,r} Among them, w ij is the four-wheel speed; Re is the effective rolling radius of the wheel; V y is the vehicle lateral speed; 2) If the load transfer index of the wheel exceeds the threshold, that is The longitudinal and lateral forces of the wheel are calculated using a nonlinear tire model, and the calculation formula is as follows: F x,ij =D x sin[C x silver,B x λ ij -AND x (B x λ ij -arctane(B x λ ij ))-+ F y,ij =D y sin[C y silver,B y α ij -AND y (B y α ij -arctane(B y α ij ))-+ Among them, D x,y is the peak factor; C x,y is the curve shape factor; E x,y is the curve curvature factor.

7. The vehicle model refinement modeling and trajectory tracking method considering tire vertical load as claimed in claim 3, characterized in that: In step S24, the vehicle dynamics model is as follows: Among them, F Xij 、F Yij , i={f,r}, j={l,r} are the longitudinal and lateral forces provided by the wheels respectively; m is the mass of the vehicle; x v ,y v are the longitudinal displacement and lateral displacement of the vehicle in the geodetic coordinate system respectively; l f , l r are the distances from the center of gravity of the vehicle to the front and rear wheels respectively; t f ,t r They are the front and rear wheelbases of the vehicle respectively.

8. The vehicle model refinement modeling and trajectory tracking method considering tire vertical load as claimed in claim 1, characterized in that: The step three comprises: The state space equation is established through the vehicle dynamics model established in step 2. The control variables, state variables and output variables of the vehicle motion controller are: u=[δ fl ,δ fr ,T fl ,T fr ,T rl ,T rr ] T Among them, T fl ,T fr ,T rl ,T rr , are the torque values ​​of the left front, right front, left rear and right rear wheels respectively, and their calculation relationship with the tire longitudinal force is: F x,ij =T ij / Re,i={f,r},j={l,r} Among them, T ij is the torque of each tire, i = {f, r} is the front and rear wheels of the vehicle, j = {l, r} is the left and right wheels of the vehicle; F x,ij is the longitudinal force of each tire; Re represents the effective rolling radius of the tire; The continuous state equation of the vehicle is discretized, and the nonlinear prediction equation for predicting the future state of the vehicle is expressed as: x(k+1)=F(x(k),u(k)),k∈Ν Based on the model predictive control principle, according to the measured value of the current control system state and the prediction model, at the current time k, the reference matrix of the predicted system's future input variables, output variables, and state variables is expressed as: Among them, N p is the prediction time domain; N c To control the time domain, N c ≤N p .

9. The vehicle model refinement modeling and trajectory tracking method considering tire vertical load as claimed in claim 1, characterized in that: The fourth step comprises: The cost function is constructed by the reference value of the vehicle's state information, the difference between the vehicle state and the expected value in the control time domain, and the change value of the control quantity: To ensure that the vehicle tracks the expected speed and expected path, the cost function J1 is expressed as: Among them, P i is the weight coefficient; N p For the prediction time domain; In order to reduce the fluctuation of the control amount, the cost functions J2 and J3 are expressed as: Among them, Q i , R i is the weight coefficient of each part of the loss function; N c To control the time domain; T fl ,T fr ,T rl ,T rr , are the torque values ​​of the left front, right front, left rear and right rear wheels respectively; Therefore, the overall cost function of the optimization problem is expressed as: J=J1+J2+J3 Set the relevant constraints of the optimization problem. Considering the physical constraints of the vehicle during driving, the optimization problem can be summarized as follows: min J(x(k),u(k))=J1+J2+J3,N c ≤N p stx(k+1)=F(x(k),u(k)),k∈N -T max ≤T ij ≤T max ,i={f,r},j={l,r} -ΔT max ≤ΔT ij ≤ΔT max -d max ≤δ fl,fr ≤δ max -Dd max ≤Δδ fl,fr ≤Δδ max Where N c To control the time domain, N p is the prediction time domain, N c ≤N p ; Solve the control quantity u and feed the solved control quantity back to the vehicle reference model to complete the closed-loop control of the vehicle.

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